Tailoring a Metabolic Model for CHO Cell-Line By Integrating Data-Inferred Metabolic Activities

CHO cells are widely used in commercial production of biotherapeutics. Despite this, CHO bioprocesses have traditionally been developed empirically, due to a limited understanding of their biology. Now, an increased knowledge of CHO cell biology can be exploited to improve production and control. A promising platform for such rational engineering is genome-scale metabolic network models, which describe metabolism mathematically. These models can predict cell-line specific metabolic features when integrated with omics data, based on key assumptions on gene expression regulation and gene-to-reaction relationships. Here, we deployed a novel approach that uses transcriptomic data to define a cells' metabolic functions, and then used these to build a metabolic model for a CHO-K1-derived industrial producer cell-line. We have used the resulting model to predict key reaction fluxes for multiple bioprocess settings, and it can be applied for rational bioprocess optimization.